Sustainability as a concept is present in most aspects of our everyday life, and industry is no exception. Likewise, there is no doubt that the necessity to produce goods in a sustainable way and to ensure that products are sustainable is gaining more and more attention from producers, customers, governments, and various organizations. Understandably, there are several ways to increase the sustainable development of industrial production. One effective tool is simulation, which can have a significant impact on improving environmental, economic, and social sustainability. This paper explores the role of simulation as a powerful scientific and engineering solution in advancing sustainability within industrial ecosystems. Its main scope is to map the existing literature on the usage of simulation as a supportive tool for achieving this goal. For this purpose, a bibliometric analysis was conducted, allowing for tailored insights into the use of simulation in sustainable production. Full article

Waste treatment and valorization have become crucial for sustainable development towards a circular economy. As an alternative, biochar production is a promising process to convert wastes into a valuable product that presents several potential applications to cope with environmental problems. Biochar in recent years has been the subject of many studies, which have leveraged the number of patents and the industrial interest in this process. Against this background, this overview aimed: (i) to identify the advances in biochar research; (ii) to assess the number of patents on biochar over the years; (iii) to look at the industrial production of biochar worldwide; (iv) to detect the potential for biochar production in Brazil regarding waste biomass availability; and (v) to discuss the potential of biochar in contributing to reach some Sustainable Development Goals (SDGs). The holistic analysis presented here suggests that progress has been made in research, patent development, and industrial implementation of biochar, and that its potential role in achieving certain SDGs is noteworthy. Therefore, this overview can be useful in guiding future research about biochar to improve the knowledge of the different branches in this field. Full article

This study aimed to assess the sorption capacity of a natural sorbent, specifically birch bark (BB), and its modification using chemical reagents, including nitric and hydrochloric acid, sodium hydroxide, and chloride. The objective of the chemical modification was to enhance the sorption capacity of the heavy metals cadmium(II), chromium(VI), and manganese(II). The most effective modification for adsorbing cadmium and manganese from aqueous solutions was achieved by treating the sorbent with a 0.1 M sodium hydroxide solution (BBNa). Conversely, in the case of chromium, each modification adversely affected its adsorption by the sorbent. Concentrations of the solutions were analyzed using atomic absorption spectrometry at appropriate time intervals. The adsorption process was described using Langmuir, Freundlich, and Temkin isotherms. The Freundlich isotherm provided the best fit for cadmium and chromium (R² = 0.988 and 0.986, respectively), while the Langmuir isotherm was most suitable for manganese (R² = 0.996). The sorption capacity varied for each metal ion: Cd (II)—33.13 mg/g, Cr (VI)—35.98 mg/g, and Mn (II)—24 mg/g for the highest concentration tested. This study employed pseudo–first-rate order, pseudo–second-rate order model kinetics, and the Weber–Morris model to examine the adsorption kinetics. The pseudo–second-rate order kinetics demonstrated the best fit (R² > 0.94) for each heavy metal, which underlines the process’s chemical nature. Full article

The main subject of the current review is a specific subtype of headache, which is related to shunt over-drainage and slit ventricle syndrome, in pediatric patients harboring an implanted shunt device for the management of hydrocephalus. This clinical entity, along with its impairment regarding the quality of life of the affected individuals, is generally underestimated. This is partly due to the absence of universally agreed-upon diagnostic criteria, as well as due to a misunderstanding of the interactions among the implicated pathophysiological mechanisms. A lot of attempts have been performed to propose an integrative model, aiming at the determination of all the offending mechanisms of the shunt over-drainage syndrome, as well as the determination of all the clinical characteristics and related symptomatology that accompany these secondary headaches. This subcategory of headache, named postural dependent headache, can be associated with nausea, vomiting, and/or radiological signs of slim ventricles and/or subdural collections. The ultimate goal of our review is to draw clinicians’ attention, especially that of those that are managing pediatric patients with permanent, long-standing, ventriculoperitoneal, or, less commonly, ventriculoatrial shunts. We attempted to elucidate all clinical and neurological characteristics that are inherently related to this type of headache, as well as to highlight the current management options. This specific subgroup of patients may eventually suffer from severe, intractable headaches, which may negatively impair their quality of daily living. In the absence of any other clinical condition that could be incriminated as the cause of the headache, shunt over-drainage should not be overlooked. On the contrary, it should be seriously taken into consideration, and its management should be added to the therapeutic armamentarium of such cases, which are difficult to be handled. Full article

This narrative review study investigates the correlations between obesity, allergies, and sleep-disordered breathing in pediatric populations. Searches for pertinent articles were conducted on the Medline PubMed Advanced Search Builder, Scopus, and Web of Science databases from unlimited to April 2024. Sleep-disordered breathing causes repeated upper airway obstructions, leading to apneas and restless sleep. Childhood obesity, which affects around 20% of children, is often associated with sleep-disordered breathing and allergies such as asthma and allergic rhinitis. It is distinguished between diet-induced obesity (resulting from excess of diet and physical inactivity) and genetic obesity (such as is seen in Down syndrome and Prader–Willi syndrome). In children with diet-induced obesity, chronic inflammation linked to weight can worsen allergies and increase the risk and severity of asthma and rhinitis. Furthermore, the nasal congestion typical of rhinitis can contribute to upper respiratory tract obstruction and obstructive sleep apnea. A vicious circle is created between asthma and sleep-disordered breathing: uncontrolled asthma and sleep-disordered breathing can worsen each other. In children with genetic obesity, despite alterations in the immune system, fewer allergies are observed compared to the broader population. The causes of this reduced allergenicity are unclear but probably involve genetic, immunological, and environmental factors. Additional research is necessary to elucidate the underlying mechanisms. The present narrative review study emphasizes the importance of jointly evaluating and managing allergies, obesity, and obstructive sleep apnea in children considering their close interconnection. Full article

Breast cancer represents a significant health concern, particularly in Saudi Arabia, where it ranks as the most prevalent cancer type among women. This study focuses on leveraging eXplainable Artificial Intelligence (XAI) techniques to predict benign and malignant breast cancer cases using various clinical and pathological features specific to Saudi Arabian patients. Six distinct models were trained and evaluated based on common performance metrics such as accuracy, precision, recall, F1 score, and AUC-ROC score. To enhance interpretability, Local Interpretable Model-Agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP) were applied. The analysis identified the Random Forest model as the top performer, achieving an accuracy of 0.72, along with robust precision, recall, F1 score, and AUC-ROC score values. Conversely, the Support Vector Machine model exhibited the poorest performance metrics, indicating its limited predictive capability. Notably, the XAI approaches unveiled variations in the feature importance rankings across models, underscoring the need for further investigation. These findings offer valuable insights into breast cancer diagnosis and machine learning interpretation, aiding healthcare providers in understanding and potentially integrating such technologies into clinical practices. Full article

The Hip Dysfunction and Osteoarthritis Outcome Score for Joint Replacement (HOOS-JR) was developed as a short-form survey to measure progress after total hip arthroplasty (THA). However, the longitudinal validity of the scale structure pertaining to the modified five-item HOOS-JR has not been assessed. Therefore, the purpose of this study was to evaluate the structural validity, longitudinal invariance properties, and latent growth curve (LGC) modeling of the modified five-item HOOS-JR in a large multi-site sample of patients who underwent a THA. A longitudinal study was conducted using data from the Surgical Outcome System (SOS) database. Confirmatory factor analyses (CFAs) were conducted to assess the structural validity and longitudinal invariance across five time points. Additionally, LGC modeling was performed to assess the heterogeneity of the recovery patterns for different subgroups of patients. The resulting CFAs met most of the goodness-of-fit indices (CFI = 0.964–0.982; IFI = 0.965–0.986; SRMR = 0.021–0.035). Longitudinal analysis did not meet full invariance, exceeding the scalar invariance model (CFI_DIFF = 0.012; χ²_DIFF test = 702.67). Partial invariance requirements were met upon release of the intercept constraint associated with item five (CFI_DIFF test = 0.010; χ²_DIFF = 1073.83). The equal means model did not pass the recommended goodness-of-fit indices (CFI_DIFF = 0.133; χ²_DIFF = 3962.49). Scores significantly changed over time, with the highest scores identified preoperatively and the lowest scores identified at 2- and 3-years postoperatively. Upon conclusion, partial scalar invariance was identified within our model. We identified that patients self-report most improvements in their scores within 6 months postoperatively. Females reported more hip disability at preoperative time points and had faster improvement as measured by the scores of the modified five-item HOOS-JR. Full article

Healthcare human resource planning is one of the biggest challenges facing the healthcare systems in many countries. Inadequate decisions in human resource planning can lead to an insufficient number of healthcare professionals then healthcare inequalities. One of the components of resource planning in the healthcare system is long-term data monitoring and the identification of potential trends. Since 1990, the number of physicians in Lithuania has decreased by 15.3% (−2266), but the decrease in the population has led to a 13.61% increase in the number of physicians per 10,000 inhabitants (5.32). During the analyzed period, the largest decrease in the number of physicians workforce by specialty was the number of medical physicians (−73.08%), epidemiology and hygiene (−69.30%), children’s diseases (−49.08%), the most increased number was of family/general practitioners (GPs), geneticists, physical medicine, and rehabilitation specialists. Since 1992, the number of visits to physicians in Lithuania, which has been decreasing for a long time, began increasing, and in 2022 (9.3 visits) it has almost reached the number of visits (9.5) per capita as in 1991. The aim of this research was to collect long-term data from various databases, summarize them, and identify possible trends and the reasons for data changes. The study analyzed data from the Lithuanian healthcare system from the Declaration of Independence of Lithuania to the last 30 years. The data includes or affects the indicators of the healthcare system, changes in population and doctors, the number of visits to doctors, the number of medical students and residents, and data determining inequalities in the healthcare system. Long-term data analysis is useful for developing a model of healthcare human resource planning and for planning healthcare resources. Full article

Background: A negative lifestyle is reported to be related to cognitive problems. However, there is little information about this in relation to university students. The objective of the present study was to investigate the association between executive functions (EFs) and lifestyle parameters (i.e., physical activity (PA), sleep duration, screen time (ST), and food habits) among Chilean university students. Methods: This cross-sectional study included a total of 150 university students (94 females and 56 males, aged 21.28 ± 3.15 and 22.18 ± 2.90 years, respectively). Cognitive outcomes were measured using the CogniFit assessment battery. Lifestyle was measured through validated questionnaires. Results: Across the total sample, attention exhibited a positive association with PA h/week (β: 24.34 95% CI: 12.46 to 36.22, p = 0.001). Additionally, coordination was positively associated with PA h/week (β: 15.06 95% CI: 0.62 to 29.50, p < 0.041). PA h/week was positively linked with reasoning (β: 20.34 95% CI: 4.52 to 36.17, p = 0.012) and perception (β: 13.81 95% CI: 4.14 to 23.49, p = 0.005). Moreover, PA h/week was significantly linked to memory (β: 23.01 95% CI: 7.62 to 38.40, p = 0.004). In terms of the EFs, PA h/week showed a positive association with cognitive flexibility (β: 45.60 95% CI: 23.22 to 67.69, p = 0.001). Conclusions: In conclusion, lifestyle (PA h/week) was positively associated with EFs. Therefore, an increase in PA levels among these students should be a target for community- and university-based interventions in order to promote cognitive development such as attention, coordination, reasoning, perception, memory, and cognitive flexibility. Full article

The development of medical image classification models necessitates a substantial number of labeled images for model training. In real-world scenarios, sample sizes are typically limited and labeled samples often constitute only a small portion of the dataset. This paper aims to investigate a collaborative similarity learning strategy that optimizes pseudo-labels to enhance model accuracy and expedite its convergence, known as the joint similarity learning framework. By integrating semantic similarity and instance similarity, the pseudo-labels are mutually refined to ensure their quality during initial training. Furthermore, the similarity score is utilized as a weight to guide samples away from misclassification predictions during the classification process. To enhance the model’s generalization ability, an adaptive consistency constraint is introduced into the loss function to improve performance on untrained datasets. The model achieved a satisfactory accuracy of 93.65% at 80% labeling ratio, comparable to supervised learning methods’ performance. Even with very low labeling ratio (e.g., 5%), the model still attained an accuracy of 74.28%. Comparison with other techniques such as Mean Teacher and FixMatch revealed that our approach significantly outperforms them in medical image classification tasks through improving accuracy by approximately 2%, demonstrating this framework’s leadership in medical image classification. Full article

Understanding breast cancer drug response mechanisms can play a crucial role in improving treatment outcomes and survival rates. Existing bioinformatics-based approaches are far from perfect and do not adopt computational methods based on advanced artificial intelligence concepts. Therefore, we introduce a novel computational framework based on an efficient support vector machine (esvm) working as follows: First, we downloaded and processed three gene expression datasets related to breast cancer responding and non-responding to treatments from the gene expression omnibus (GEO) according to the following GEO accession numbers: GSE130787, GSE140494, and GSE196093. Our method esvm is formulated as a constrained optimization problem in its dual form as a function of λ. We recover the importance of each gene as a function of λ, y, and x. Then, we select p genes out of n, which are provided as input to enrichment analysis tools, Enrichr and Metascape. Compared to existing baseline methods, including deep learning, results demonstrate the superiority and efficiency of esvm, achieving high-performance results and having more expressed genes in well-established breast cancer cell lines, including MD-MB231, MCF7, and HS578T. Moreover, esvm is able to identify (1) various drugs, including clinically approved ones (e.g., tamoxifen and erlotinib); (2) seventy-four unique genes (including tumor suppression genes such as TP53 and BRCA1); and (3) thirty-six unique TFs (including SP1 and RELA). These results have been reported to be linked to breast cancer drug response mechanisms, progression, and metastasizing. Our method is available publicly on the maGENEgerZ web server. Full article

Wind field characteristics in a complex topography are significantly influenced by the nature of the surrounding terrains. This study employs onsite measurements to investigate the wind field characteristics at a towering peak protruding out of a steep mountainside, where butterfly−lookalike landscape platform will be constructed; the impact of the surrounding topography on the wind flow is highlighted. The results showed that the blocking effect of the mountains in the mountainous side of the valley caused a significant drop in the mean wind speed from that direction. The stationary test (reverse arrangement test) indicated that the wind speed had a strong nonstationary characteristic, necessitating the employment of a steady and nonstationary wind speed model to assess the wind turbulence characteristics. The three directions’ wind turbulence integral scales were critically influenced by the occurrence of the wind speedup effect, unexpectedly resulting in the vertical turbulence integral scale being the greatest of the three. Furthermore, the measured wind turbulence properties under both wind speed models showed certain variations from the recommended specifications. Consequently, the impact of the local terrain and the speedup effect on the wind characteristics must be thoroughly evaluated to ensure the structural stability of structures installed at a similar topography. Full article

Due to the present worldwide economic development, there is an increasing need to follow the financial health of companies in individual sectors to avoid possible decline and bankruptcy. The goal of this contribution is to find out the influence of the pandemic on the economic situation in the mining industry as the primary sector, in connection with the construction industry as the secondary sector. The research is carried out through economic and financial indicators, which mostly influence the potential crisis of companies. The results show that the mining industry and construction sectors managed to avoid the heavy decline and bankruptcy of certain organizations in the industries. Such results can be used for forecasting and modeling the socio-economic development of regions and countries. The growth of the analyzed industries could contribute to the sustainable development in the country. Full article

(1) Objectives: A divergence in self- and preceptor-evaluations of clinical skills has been noted during Advanced Pharmacy Practice Experiences (APPEs). The goal of this study was to determine the domains of overestimation of clinical skills by students during their APPE rotations. (2) Methods: Preceptor-assigned grades for APPE rotations from 2017–2022 were analyzed to identify instances of letter grade B or lower. The self- and preceptor-evaluations of APPE rotation were compared to determine the domains of divergence in evaluation between students and preceptors. (3) Results: Between 2017 and 2022, 305 student APPE rotations were graded as B or lower (~14%) by the preceptors. A statistically significant difference was noted between self- and preceptor-assigned letter grades across all practice settings including ambulatory patient care, community pharmacy, general medicine patient care, hospital/health system pharmacy, and special population patient care APPE rotations. In addition, examining the self- and preceptor evaluation rubric for these rotations revealed a statistically significant overestimation of clinical skills by students in all 9 domains of APPE evaluation. Finally, the divergence in the rating of clinical skills between student- and preceptor evaluation was found to be highest in the domains of planning and follow-up of patient care, disease knowledge, and communication with patients. (4) Conclusions: Students who fail to exhibit exemplary practice readiness during APPEs tend to overestimate their clinical skills in all domains of APPE evaluation. The results from our study support the need for additional avenues to assist in the identification of deficits in student learning before APPEs to increase their self-awareness (metacognition). Full article

Argemone mexicana L. has been used in traditional Mexican medicine. Among its bioactive constituents, berberine (BER) has garnered attention for its cytotoxic properties against different tumor cell lines. This study investigates the in vitro toxicity against HEP-G2 (human hepatocellular carcinoma) and murine lymphoma (L5178Y-R) cells using the MTT assay of the methanol extract (AmexM), sub-partitions of A. mexicana, and BER. Selectivity indices (SIs) were determined by comparing their cytotoxic effects on VERO (monkey kidney epithelial) and PBMC (human peripheral blood mononuclear) non-tumoral cells. Additionally, the anti-hemolytic effect of these treatments was assessed using the AAPH method. The treatment with the most promising activity against tumor cells and anti-hemolytic efficacy underwent further evaluation for toxicity in Artemia salina and antioxidant activities using DPPH, ABTS, and FRAP assays. BER demonstrated an IC₅₀ = 56.86 µg/mL in HEP-G2 cells and IC₅₀ < 5.0 µg/mL in L5178Y-R cells, with SI values of 15.97 and >5.40 in VERO and PBMC cells, respectively. No significant hemolytic effects were observed, although AmexM and BER exhibited the highest anti-hemolytic activity. BER also demonstrated superior antioxidant efficacy, with lower toxicity in A. salina nauplii compared to the control. Additionally, BER significantly attenuated nitric oxide production. This study highlights the antiproliferative effects of A. mexicana, particularly BER, against HEP-G2 and L5178Y-R tumor cell lines, along with its selectivity towards normal cells. Furthermore, its anti-hemolytic and antioxidant potentials were demonstrated, suggesting that BER is a promising candidate for potent chemotherapeutic agents. Full article

Southern Min is generally known for not using classifiers [CL] for expressing definiteness/indefiniteness as it is associated with the bare classifier construction [CL N]. This paper offers evidence from Xiamen Southern Min (XSM) that the use of a specific classifier vs. the general classifier é contributes to referentiality in an alternative way by supporting object identification as it is due to the semantic specificity present in specific classifiers and absent in the general classifier. In a dialogic cognitive experiment adapted from the “Hidden color-chips” task (Enfield and Bohnemeyer 2001), 18 participants had to manipulate their addressees’ attention toward various objects situated in their immediate physical space through language as well as deictic gestures. The objects were associated with different specific classifiers or with the general classifier, and they were arranged according to the factors of (a) distance from speaker, (b) visibility for speaker, and (c) uniqueness (adjacency of similar items). The results show, among other things, that there is a higher tendency to use the specific CL in the [demonstrative CL N] construction if adjacent similar objects [−unique] are too far away from the speaker for clear identification by a demonstrative or a pointing gesture. This is seen as a last-resort strategy for creating contrast. Further corroboration comes from the use of specific classifiers in later mentions after the general CL failed to achieve clear identification. These findings can be situated in the broader context of other languages with classifiers in contrastive function (Thai, Vietnamese, and Ponapean) and they show the relevance of using dialogic texts for modeling classifier selection in contrast to narrative texts. Finally, dialogic contexts may serve as bridging contexts for grammaticalization from numeral classifiers to definiteness markers. Full article

Multi-cropping is becoming an increasingly popular technique in agriculture to tackle major and complex agroecosystem problems such as biodiversity and soil fertility loss, erosion and degradation, increased greenhouse gas emissions, etc. Comprehensively assessing the impact of multi-cropping intensity on agroecosystems is a new and still under-researched approach that can provide a better understanding of the impact of individual indicators on the overall functioning of biodiverse agroecosystems. Data from a stationary field experiment using multi-cropping at the Vytautas Magnus University Experimental Station between 2020 and 2022 were used to carry out this study. The study included maize, hemp, and faba bean as single, binary, and ternary crops. A complex assessment approach (CEI value) was used to determine the impact of these crops on the agroecosystem, the interrelationships between the main indicators, and the strength of their effects. It was found that the ternary maize–hemp–faba bean crop had the most positive effect on the agroecosystem. The effectiveness of other crops was 2 to 35% less. The lowest value was calculated for the maize–faba bean crop. Full article

Benzoxazinoids (BXs) are tryptophan-derived indole metabolites and play a role in various physiological processes, such as auxin metabolism. Auxin is essential in the process of somatic embryogenesis (SE) in plants. In this study, we used bioinformatics, transcriptome data, exogenous treatment experiments, and qPCR analysis to study the evolutionary pattern of Bx genes in green plants, the regulatory mechanism of DlBx genes during early SE, and the effect of 2,4-dihydroxy-7-methoxy-1,4-benzoxazine-3-one (DIMBOA) on the early SE in Dimocarpus longan Lour. The results showed that 27 putative DlBxs were identified in the longan genome; the Bx genes evolved independently in monocots and dicots, and the main way of gene duplication for the DlBx was tandem duplication (TD) and the DlBx were strongly constrained by purification selection during evolution. The transcriptome data indicated varying expression levels of DlBx during longan early SE, and most DlBxs responded to light, temperature, drought stress, and 2,4-dichlorophenoxyacetic acid (2,4-D) treatment; qRT-PCR results showed DlBx1, DlBx6g and DlBx6h were responsive to auxin, and treatment with 0.1mg/L DIMBOA for 9 days significantly upregulated the expression levels of DlBx1, DlBx3g, DlBx6c, DlBx6f, DlB6h, DlBx7d, DlBx8, and DlBx9b. The correlation analysis showed a significantly negative correlation between the expression level of DlBx1 and the endogenous IAA contents; DIMBOA significantly promoted the early SE and significantly changed the endogenous IAA content, and the IAA content increased significantly at the 9th day and decreased significantly at the 13th day. Therefore, the results suggested that DIMBOA indirectly promote the early SE by changing the endogenous IAA content via affecting the expression level of DlBx1 and hydrogen peroxide (H₂O₂) content in longan. Full article

Agave tequilana Weber var. Blue is used as the primary raw material in tequila production due to its fructans (inulin) content. This study evaluates the formulation of a plant-growth-promoting bacteria (PGPB) consortium (Pseudomonas sp. and Shimwellia sp.) to increase sugars in A. tequilana under field conditions. A total of three doses were tested: low (5 L ha⁻¹), medium (10 L ha⁻¹), and high (15 L ha⁻¹), with a cellular density of 1 × 10⁸ CFU mL⁻¹ and one control treatment (without application). Total reducing sugars (TRS), inulin, sucrose, glucose, fructose, and plant growth were measured in agave plants aged 4–5 years at 0 (T0), 3 (T3), 6 (T6), and 12 (T12) months. Yield was recorded at T12. The TRS increased by 3%, and inulin by 5.3% in the high-dose treatment compared to the control at T12. Additionally, a low content of sucrose, glucose, and fructose (approximately 1%) was detected. At T12, the weight of agave heads increased by 31.2% in the medium dose and 22.3% in the high dose compared to the control. The high dose provided a higher inulin content. The A. tequilana plants were five years old and exhibited growth comparable to the standards for 6–7-year-old plants. This study demonstrates a sustainable strategy for tequila production, optimizing the use of natural resources and enhancing industry performance through increased sugar content and yield. Full article

An hourglass-shaped magnetic field pattern arises naturally from the gravitational collapse of a star-forming gas cloud. Most studies have focused on the prestellar collapse phase, when the structure has a smooth and monotonic radial profile. However, most observations target dense clouds that already contain a central protostar, and possibly a circumstellar disk. We utilize an analytic treatment of the magnetic field along with insights gained from simulations to develop a more realistic magnetic field model for the protostellar phase. Key elements of the model are a strong radial magnetic field in the region of rapid collapse, an off-center peak in the magnetic field strength (a consequence of magnetic field dissipation in the circumstellar disk), and a strong toroidal field that is generated in the region of rapid collapse and outflow generation. A model with a highly pinched and twisted magnetic field pattern in the inner collapse zone facilitates the interpretation of magnetic field patterns observed in protostellar clouds. Full article

The application of artificial intelligence (AI) in programming assistance has garnered researchers’ attention for its potential to reduce learning costs for users, increase work efficiency, and decrease repetitive coding tasks. However, given the novelty of AI Coding Assistant Tools (AICATs), user acceptance is currently limited, and the factors influencing this phenomenon are unclear. This study proposes an expanded model based on the Technology Acceptance Model (TAM) that incorporates the characteristics of AICAT users to explore the key factors affecting college students’ willingness to use AICATs. Utilizing a survey methodology, 303 Chinese participants completed the questionnaire. Factor analysis and Structural Equation Modeling (SEM) results indicate that users’ dependence worry (DW) about AICATs positively affects perceived risk (PR), which in turn negatively impacts perceived usefulness (PU) and perceived ease of use (PEOU), thus reducing user willingness to use. Dependence concerns also negatively impact perceived trust (PT), while PT positively affects PU and PEOU, thereby enhancing willingness to use. Additionally, a user’s self-efficacy (SE) negatively impacts DW and positively affects PEOU. This study discusses the potential significance of these findings and offers suggestions for AICAT developers to foster and promote widespread use. Full article

Multiple research directions have been proposed to study the information structure of Reddit. One of them is to model inter-subreddit relations but modeling user interactions in the form of a graph. Building upon prior work centered on political subreddits using pre-2020 data, we expand this investigation to include a more extensive dataset spanning 2022 and encompassing diverse topic areas. Employing NLP techniques such as text embeddings, we model subreddit content directly and construct a subreddit graph network based on cosine similarity. Community detection using the Louvain method reveals distinct subreddits and allows the analysis of inter-community connections via previous works’ concepts of “bridges” and “gateways”. Surprisingly, our findings indicate redundancy between bridges and gateways in the utilized dataset. Therefore, we introduce a new concept, “highways”. Highways, representing the most traversed paths between subreddits, unveil insights not captured by previous analyses, underscoring the significance of novel conceptual frameworks in uncovering latent knowledge within Reddit’s online community structures. Full article